A Survey on PiCode: Picture-Embedding 2D Barcode

In this Review paper discusses about the last few years, conventional Two-Dimensional (2D) barcodes and some existing beautified QR codes. Quick Response (QR) code is widely used in many applications such as marketing, for industrial applications, retail applications, health care applications, manufacturing, and product tracking etc.This paper explains the basic concept of QR images, i.e. a recently proposed beautified QR code. We focus on revising preprocessing methods by proposing block division and source & channel coding methods. In the traditional decoding procedure decoding steps consist of image binarization, corner detection, perspective transformation and error correction. So the existing barcodes have some limitations, so the new picture-embedding 2D barcode system: Picode proposed. PiCode technology improves the aesthetic value of the picture embedded barcode. To preserve both the perceptual quality of the embedded image and the decoding robustness of the encoded message PiCode is designed with careful considerations. Advantage of using PiCode in advertisement business to link customers in a more interactive, interesting, and unique way. So the PiCode enable pictures/logo to be integrated with a 2D barcode to achieve enhanced visual appearance and high decoding reliability

Computer vision reading on stickers and direct part marking on horticultural products : challenges and possible solutions

Traceability of products from production to the consumer has led to a technological advancement in product identification. There has been development from the use of traditional one-dimensional barcodes (EAN-13, Code 128, etc.) to 2D (two-dimensional) barcodes such as QR (Quick Response) and Data Matrix codes. Over the last two decades there has been an increased use of Radio Frequency Identification (RFID) and Direct Part Marking (DPM) using lasers for product identification in agriculture. However, in agriculture there are still considerable challenges to adopting barcodes, RFID and DPM technologies, unlike in industry where these technologies have been very successful. This study was divided into three main objectives. Firstly, determination of the effect of speed, dirt, moisture and bar width on barcode detection was carried out both in the laboratory and a flower producing company, Brandkamp GmbH. This study developed algorithms for automation and detection of Code 128 barcodes under rough production conditions. Secondly, investigations were carried out on the effect of low laser marking energy on barcode size, print growth, colour and contrast on decoding 2D Data Matrix codes printed directly on apples. Three different apple varieties (Golden Delicious, Kanzi and Red Jonaprince) were marked with various levels of energy and different barcode sizes. Image processing using Halcon 11.0.1 (MvTec) was used to evaluate the markings on the apples. Finally, the third objective was to evaluate both algorithms for 1D and 2D barcodes. According to the results, increasing the speed and angle of inclination of the barcode decreased barcode recognition. Also, increasing the dirt on the surface of the barcode resulted in decreasing the successful detection of those barcodes. However, there was 100% detection of the Code 128 barcode at the company’s production speed (0.15 m/s) with the proposed algorithm. Overall, the results from the company showed that the image-based system has a future prospect for automation in horticultural production systems. It overcomes the problem of using laser barcode readers. The results for apples showed that laser energy, barcode size, print growth, type of product, contrast between the markings and the colour of the products, the inertia of the laser system and the days of storage all singularly or in combination with each other influence the readability of laser Data Matrix codes and implementation on apples. There was poor detection of the Data Matrix code on Kanzi and Red Jonaprince due to the poor contrast between the markings on their skins. The proposed algorithm is currently working successfully on Golden Delicious with 100% detection for 10 days using energy 0.108 J mm-2 and a barcode size of 10 × 10 mm2. This shows that there is a future prospect of not only marking barcodes on apples but also on other agricultural products for real time production

High Capacity Analog Channels for Smart Documents

Widely-used valuable hardcopy documents such as passports, visas, driving licenses, educational certificates, entrance-passes for entertainment events etc. are conventionally protected against counterfeiting and data tampering attacks by applying analog security technologies (e.g. KINEGRAMS®, holograms, micro-printing, UV/IR inks etc.). How-ever, easy access to high quality, low price modern desktop publishing technology has left most of these technologies ineffective, giving rise to high quality false documents. The higher price and restricted usage are other drawbacks of the analog document pro-tection techniques. Digital watermarking and high capacity storage media such as IC-chips, optical data stripes etc. are the modern technologies being used in new machine-readable identity verification documents to ensure contents integrity; however, these technologies are either expensive or do not satisfy the application needs and demand to look for more efficient document protection technologies. In this research three different high capacity analog channels: high density data stripe (HD-DataStripe), data hiding in printed halftone images (watermarking), and super-posed constant background grayscale image (CBGI) are investigated for hidden com-munication along with their applications in smart documents. On way to develop high capacity analog channels, noise encountered from printing and scanning (PS) process is investigated with the objective to recover the digital information encoded at nearly maximum channel utilization. By utilizing noise behaviour, countermeasures against the noise are taken accordingly in data recovery process. HD-DataStripe is a printed binary image similar to the conventional 2-D barcodes (e.g. PDF417), but it offers much higher data storage capacity and is intended for machine-readable identity verification documents. The capacity offered by the HD-DataStripe is sufficient to store high quality biometric characteristics rather than extracted templates, in addition to the conventional bearer related data contained in a smart ID-card. It also eliminates the need for central database system (except for backup record) and other ex-pensive storage media, currently being used. While developing novel data-reading tech-nique for HD-DataStripe, to count for the unavoidable geometrical distortions, registra-tion marks pattern is chosen in such a way so that it results in accurate sampling points (a necessary condition for reliable data recovery at higher data encoding-rate). For more sophisticated distortions caused by the physical dot gain effects (intersymbol interfer-ence), the countermeasures such as application of sampling theorem, adaptive binariza-tion and post-data processing, each one of these providing only a necessary condition for reliable data recovery, are given. Finally, combining the various filters correspond-ing to these countermeasures, a novel Data-Reading technique for HD-DataStripe is given. The novel data-reading technique results in superior performance than the exist-ing techniques, intended for data recovery from printed media. In another scenario a small-size HD-DataStripe with maximum entropy is used as a copy detection pattern by utilizing information loss encountered at nearly maximum channel capacity. While considering the application of HD-DataStripe in hardcopy documents (contracts, official letters etc.), unlike existing work [Zha04], it allows one-to-one contents matching and does not depend on hash functions and OCR technology, constraints mainly imposed by the low data storage capacity offered by the existing analog media. For printed halftone images carrying hidden information higher capacity is mainly attributed to data-reading technique for HD-DataStripe that allows data recovery at higher printing resolution, a key requirement for a high quality watermarking technique in spatial domain. Digital halftoning and data encoding techniques are the other factors that contribute to data hiding technique given in this research. While considering security aspects, the new technique allows contents integrity and authenticity verification in the present scenario in which certain amount of errors are unavoidable, restricting the usage of existing techniques given for digital contents. Finally, a superposed constant background grayscale image, obtained by the repeated application of a specially designed small binary pattern, is used as channel for hidden communication and it allows up to 33 pages of A-4 size foreground text to be encoded in one CBGI. The higher capacity is contributed from data encoding symbols and data reading technique

QR codes decoder

The aim of this project is to develop a device that demonstrates the ability to read barcodes, and is also capable of detecting and analysing QR codes from a picture

Diffractive nano-structures as optical visual and machine readable features

With the help of nano-fabrication and nano-optical structures a method for data storage is presented. The information in this method is encoded and represented in a multi-state system where colors or wavelengths are used as variables. The high resolving power of nano-scale diffraction grating has enabled the detection of distinguishable colors (or wavelengths) and that in turn is used to improve the storage capability of the presented system as well as achieving a natural physical compression. The data in this method are represented physically. This method offers a good data density and creates a secure system for authentication. It has both color change effect, which can be used for the first level of authentication and machine readability. In addition, by using nano-diffractive features, type of diffraction grating is designed which is capable of holding the same color for a large viewing angle. By using materials with a high refractive index a system is introduced in which images can be recorded and perceived in a 3D like manner similar to what is found in holograms recorded on film

An Architecture for Biometric Electronic Identification Document System Based on Blockchain †

This paper proposes an architecture for biometric electronic identification document (e-ID) system based on Blockchain for citizens identity verification in transactions corresponding to the notary, registration, tax declaration and payment, basic health services and registration of economic activities, among others. To validate the user authentication, a biometric e-ID system is used to avoid spoofing and related attacks. Also, to validate the document a digital certificate is used with the corresponding public and private key for each citizen by using a user’s PIN. The proposed transaction validation process was implemented on a Blockchain system in order to record and verify the transactions made by all citizens registered in the electoral census, which guarantees security, integrity, scalability, traceability, and no-ambiguity. Additionally, a Blockchain network architecture is presented in a distributed and decentralized way including all the nodes of the network, database and government entities such as national register and notary offices. The results of the application of a new consensus algorithm to our Blockchain network are also presented showing mining time, memory and CPU usage when the number of transactions scales up

Image pre-processing to improve data matrix barcode read rates

The main goal of this study is to research image processing methods in attempts to develop a robust approach to image pre-preprocessing of Data Matrix barcode images that will improve barcode read rates in an open source fashion. This is demonstrated by element state classification to re-create the ideal binary matrix corresponding to the intended barcode layout through pattern recognition theory. The research consisted of implementing and evaluating the effectiveness of many image processing algorithms types, as well as evaluating key features that clearly delineate different element states. The algorithms developed highlight the use of morphological erosion and region growing for object segmentation and edge analysis and Fisher\u27s Linear Discriminant as a means for element classification. The results demonstrate successful barcode binarization for ideal barcodes with improved read rates in most cases. The techniques developed here provide ground work for a test bed environment to continue improvements by analyzing non-ideal barcodes for additional robustness

Design and Implementation of the Embedded 2D Multi-code Image Identification System

近年来，二维条码技术广泛应用于交通运输和生产自动化等领域，它实现了信息的快速、准确获取与传输。利用摄像头拍摄条码图像，然后在嵌入式平台上进行软件解码的条码识读方式，已逐渐取代利用专用设备识读的方式，但是，光照、畸变、背景噪声等因素严重影响条码图像的质量，增加了条码定位的难度。为了提高条码识别的速度和准确率，实现实时识别，本文设计并实现了基于嵌入式平台利用图像处理算法识别多条码的识别系统。 本文的主要工作成果如下： （1）设计并实现DM码、QR码识别系统。根据DM码、QR码的符号结构特点，首先提取二值图像中的连通区，计算连通区凸包，合并相互嵌入的连通区以得到DM码的条码区域；而在定位QR码时...In recent years, the 2D barcodes have been more and more widely used in the fields of transportation and automatic production; it makes acquiring and transmittimg information more quickly and accurately. Capturing the barcode images with digital camera and then decoding them using the software running on embedded platform have been replacing the traditional special hardware, however, the image qua...学位：工学硕士院系专业：信息科学与技术学院电子工程系_电路与系统学号：2312008115317

Codificação LDPC para aplicações em códigos de barra 2D coloridos

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Elétrica, Florianópolis, 2011Nesta tese, aborda-se o armazenamento de informação em códigos de barra 2D coloridos, os quais devem ser robustos à impressão seguida de digitalização através de um scanner. Estes dois processos geram uma distorção (ruído), fazendo com que o código de barra obtido na saída do scanner seja diferente daquele original enviado. Isso define um modelo de canal de comunicação, que recebe o nome de canal PS (print and scan). A contribuição desta tese é propor códigos corretores de erros para proteger os códigos de barra 2D das adversidades do canal PS. Em particular, códigos LDPC são investigados. Um estudo foi realizado a partir do qual identificou-se que o canal PS é um caso particular do modelo de canal Gaussiano multidimensional assimétrico aditivo (AWAMGN). As capacidades de canal (ou taxas alcançáveis) do canal PS são obtidas, o que estabelece um limite para as taxas máximas que os códigos LDPC podem ter para se ter uma probabilidade de erro próxima de zero. Para essas taxas, códigos LDPC são projetados. A otimização dos códigos é feita através do método de curvas de transferência de informação extrínseca (EXIT charts). No decorrer deste estudo, um novo codificador para códigos LDPC é proposto. Este codificador apresenta complexidade de codificação linear no comprimento da palavra-código. Novos códigos LDPC otimizados especialmente para o canal PS são propostos, e seu desempenho (probabilidade de erro) é avaliado através de simulações computacionais. Por fim, os resultados são comentados, discutidos e novas ideias para pesquisas relacionadas são apresentadas

Computer Vision and Image Processing Techniques for Mobile Applications

Camera phones have penetrated every corner of society and have become a focal point for communications. In our research we extend the traditional use of such devices to help bridge the gap between physical and digital worlds. Their combined image acquisition, processing, storage, and communication capabilities in a compact, portable device make them an ideal platform for embedding computer vision and image processing capabilities in the pursuit of new mobile applications. This dissertation is presented as a series of computer vision and image processing techniques together with their applications on the mobile device. We have developed a set of techniques for ego-motion estimation, enhancement, feature extraction, perspective correction, object detection, and document retrieval that serve as a basis for such applications. Our applications include a dynamic video barcode that can transfer significant amounts of information visually, a document retrieval system that can retrieve documents from low resolution snapshots, and a series of applications for the users with visual disabilities such as a currency reader. Solutions for mobile devices require a fundamentally different approach than traditional vision techniques that run on traditional computers, so we consider user-device interaction and the fact that these algorithms must execute in a resource constrained environment. For each problem we perform both theoretical and empirical analysis in an attempt to optimize performance and usability. The thesis makes contributions related to efficient implementation of image processing and computer vision techniques, analysis of information theory, feature extraction and analysis of low quality images, and device usability